Precision machine vision inspection systems (or “vision systems” for short) can be utilized to obtain precise dimensional measurements of inspected objects and to inspect various other object characteristics. Such systems may include a computer, a camera and optical system, and a precision stage that is movable in multiple directions so as to allow the camera to scan the features of a workpiece that is being inspected. One exemplary prior art system that is commercially available is the QUICK VISION® series of PC-based vision systems and QVPAK® software available from Mitutoyo America Corporation (MAC), located in Aurora, Ill. The features and operation of the QUICK VISION® series of vision systems and the QVPAK® software are generally described, for example, in the QVPAK 3D CNC Vision Measuring Machine User's Guide, published January 2003, and the QVPAK 3D CNC Vision Measuring Machine Operation Guide, published September 1996, each of which is hereby incorporated by reference in their entirety. This product, as exemplified by the QV-302 Pro model, for example, is able to use a microscope-type optical system to provide images of a workpiece at various magnifications, and a motion control system to move the stage as necessary to traverse the workpiece surface and inspect and measure features that fall beyond the limits of any single video image.
Machine vision inspection systems generally utilize automated video inspection. U.S. Pat. No. 6,542,180 teaches various aspects of such automated video inspection and is incorporated herein by reference in its entirety. As taught in the '180 patent, automated video inspection metrology instruments generally have a programming capability that allows an automatic inspection event sequence to be defined by the user for each particular workpiece configuration. This can be implemented by text-based programming, for example, or through a recording mode which progressively “learns” the inspection event sequence by storing a sequence of machine control instructions corresponding to a sequence of inspection operations performed by a user, or through a combination of both methods. Such a recording mode is often referred to as “learn mode” or “training mode.” Once the inspection event sequence is defined in “learn mode,” such a sequence can then be used to automatically acquire (and additionally analyze or inspect) images of a workpiece during “run mode.”
The machine control instructions including the specific inspection event sequence (i.e., how to acquire each image and how to analyze/inspect each acquired image) are generally stored as a “part program” or “workpiece program” that is specific to the particular workpiece configuration. For example, a part program defines how to acquire each image, such as how to position the camera relative to the workpiece, at what lighting level, at what magnification level, etc. Further, the part program defines how to analyze/inspect an acquired image, for example, by using one or more video tools such as edge/boundary detection video tools.
Video tools may be used manually to accomplish manual inspection and/or machine control operations. Also, their set-up parameters and operation can be recorded during learn mode, in order to create automatic inspection programs, or “part programs”. Such tools may include, for example, edge/boundary detection tools, shape or pattern matching tools, dimension measuring tools, coordinate establishing tools, and the like. For example, such tools are routinely used in a variety of commercially available machine vision inspection systems, such as the QUICK VISION® series of vision systems and the associated QVPAK® software, discussed above.
General purpose visions systems such as Quick Vision™ frequently include a lens turret with lenses of various magnifications. It is common to inspect various aspects of a single workpiece or object using the various magnifications. Furthermore, in industrial inspection environments, very large workpieces are common. A single video image typically encompasses only a portion of the workpiece being observed or inspected, given the desired magnification, measurement resolution, and physical size limitations of such systems. In such cases, “navigation” to various microscopic features to be inspected on a workpiece can be difficult, particularly when the field of view is small compared to the size or distribution of the features to be inspected, and particularly when a number of confusingly similar or identical features are included on the workpiece. In general-purpose visions systems, during learn mode and/or manual operation, it has been conventional to navigate to view particular features on a workpiece either manually, by trial and error, or based on user knowledge of the workpiece design. However, manual navigation may be both slow and prone to errors in distinguishing between similar features.
Alternatively, user interfaces for semi-automatically navigating based on CAD images, or workpiece drawings, or the like, are known. However, in many cases CAD data or workpiece drawings may not exist, or may be in a format that is incompatible with such user interfaces. Also, the differences between the representation of a feature in a CAD-based user interface and the corresponding actual instance of the corresponding feature in a real workpiece image may limit the utility or application of such a CAD interface. For these and other reasons, a more convenient, realistic, and intuitive user interface that enhances the navigation and inspection programming related to relatively small features of relatively large workpieces would desirable.